BUG: fixed model serve fail with HTTP 400 on Bad Request.

mlflow/pyfunc/scoring_server/__init__.py

@@ -41,7 +41,7 @@
     from mlflow.pyfunc import load_model, PyFuncModel
 except ImportError:
     from mlflow.pyfunc import load_pyfunc as load_model
-from mlflow.protos.databricks_pb2 import MALFORMED_REQUEST, BAD_REQUEST
+from mlflow.protos.databricks_pb2 import BAD_REQUEST
 from mlflow.server.handlers import catch_mlflow_exception
 
 try:
@@ -87,7 +87,7 @@ def infer_and_parse_json_input(json_input, schema: Schema = None):
                 "Failed to parse input from JSON. Ensure that input is a valid JSON"
                 " formatted string."
             ),
-            error_code=MALFORMED_REQUEST,
+            error_code=BAD_REQUEST,
         )
 
     if isinstance(decoded_input, list):
@@ -97,7 +97,10 @@ def infer_and_parse_json_input(json_input, schema: Schema = None):
             try:
                 return parse_tf_serving_input(decoded_input, schema=schema)
             except MlflowException as ex:
-                _handle_serving_error(error_message=(ex.message), error_code=MALFORMED_REQUEST)
+                _handle_serving_error(
+                    error_message=(ex.message),
+                    error_code=BAD_REQUEST,
+                )
         else:
             return parse_json_input(json_input=json_input, orient="split", schema=schema)
     else:
@@ -106,7 +109,7 @@ def infer_and_parse_json_input(json_input, schema: Schema = None):
                 "Failed to parse input from JSON. Ensure that input is a valid JSON"
                 " list or dictionary."
             ),
-            error_code=MALFORMED_REQUEST,
+            error_code=BAD_REQUEST,
         )
 
 
@@ -129,7 +132,7 @@ def parse_json_input(json_input, orient="split", schema: Schema = None):
                 " produced using the `pandas.DataFrame.to_json(..., orient='{orient}')`"
                 " method.".format(orient=orient)
             ),
-            error_code=MALFORMED_REQUEST,
+            error_code=BAD_REQUEST,
         )
 
 
@@ -148,7 +151,7 @@ def parse_csv_input(csv_input):
                 " a valid CSV-formatted Pandas DataFrame produced using the"
                 " `pandas.DataFrame.to_csv()` method."
             ),
-            error_code=MALFORMED_REQUEST,
+            error_code=BAD_REQUEST,
         )
 
 
@@ -173,7 +176,7 @@ def parse_split_oriented_json_input_to_numpy(json_input):
                 " produced using the `pandas.DataFrame.to_json(..., orient='split')`"
                 " method."
             ),
-            error_code=MALFORMED_REQUEST,
+            error_code=BAD_REQUEST,
         )
 
 

tests/models/test_cli.py

@@ -34,7 +34,7 @@
     get_safe_port,
     pyfunc_serve_and_score_model,
 )
-from mlflow.protos.databricks_pb2 import ErrorCode, MALFORMED_REQUEST
+from mlflow.protos.databricks_pb2 import ErrorCode, BAD_REQUEST
 from mlflow.pyfunc.scoring_server import (
     CONTENT_TYPE_JSON_SPLIT_ORIENTED,
     CONTENT_TYPE_JSON,
@@ -478,9 +478,11 @@ def _validate_with_rest_endpoint(scoring_proc, host_port, df, x, sk_model, enabl
         # Try examples of bad input, verify we get a non-200 status code
         for content_type in [CONTENT_TYPE_JSON_SPLIT_ORIENTED, CONTENT_TYPE_CSV, CONTENT_TYPE_JSON]:
             scoring_response = endpoint.invoke(data="", content_type=content_type)
-            assert scoring_response.status_code == 500, (
-                "Expected server failure with error code 500, got response with status code %s "
-                "and body %s" % (scoring_response.status_code, scoring_response.text)
+            expected_status_code = 500 if enable_mlserver else 400
+            assert scoring_response.status_code == expected_status_code, (
+                "Expected server failure with error code %s, got response with status code %s "
+                "and body %s"
+                % (expected_status_code, scoring_response.status_code, scoring_response.text)
             )
 
             if enable_mlserver:
@@ -491,6 +493,6 @@ def _validate_with_rest_endpoint(scoring_proc, host_port, df, x, sk_model, enabl
 
             scoring_response_dict = json.loads(scoring_response.content)
             assert "error_code" in scoring_response_dict
-            assert scoring_response_dict["error_code"] == ErrorCode.Name(MALFORMED_REQUEST)
+            assert scoring_response_dict["error_code"] == ErrorCode.Name(BAD_REQUEST)
             assert "message" in scoring_response_dict
             assert "stack_trace" in scoring_response_dict

tests/pyfunc/test_scoring_server.py

@@ -15,7 +15,7 @@
 import mlflow.pyfunc.scoring_server as pyfunc_scoring_server
 import mlflow.sklearn
 from mlflow.models import ModelSignature, infer_signature
-from mlflow.protos.databricks_pb2 import ErrorCode, MALFORMED_REQUEST, BAD_REQUEST
+from mlflow.protos.databricks_pb2 import ErrorCode, BAD_REQUEST
 from mlflow.pyfunc import PythonModel
 from mlflow.pyfunc.scoring_server import get_cmd
 from mlflow.types import Schema, ColSpec, DataType
@@ -107,7 +107,7 @@ def test_scoring_server_responds_to_invalid_json_input_with_stacktrace_and_error
     )
     response_json = json.loads(response.content)
     assert "error_code" in response_json
-    assert response_json["error_code"] == ErrorCode.Name(MALFORMED_REQUEST)
+    assert response_json["error_code"] == ErrorCode.Name(BAD_REQUEST)
     assert "message" in response_json
     assert "stack_trace" in response_json
 
@@ -119,7 +119,7 @@ def test_scoring_server_responds_to_invalid_json_input_with_stacktrace_and_error
     )
     response_json = json.loads(response.content)
     assert "error_code" in response_json
-    assert response_json["error_code"] == ErrorCode.Name(MALFORMED_REQUEST)
+    assert response_json["error_code"] == ErrorCode.Name(BAD_REQUEST)
     assert "message" in response_json
     assert "stack_trace" in response_json
 
@@ -138,7 +138,7 @@ def test_scoring_server_responds_to_malformed_json_input_with_stacktrace_and_err
     )
     response_json = json.loads(response.content)
     assert "error_code" in response_json
-    assert response_json["error_code"] == ErrorCode.Name(MALFORMED_REQUEST)
+    assert response_json["error_code"] == ErrorCode.Name(BAD_REQUEST)
     assert "message" in response_json
     assert "stack_trace" in response_json
 
@@ -159,7 +159,7 @@ def test_scoring_server_responds_to_invalid_pandas_input_format_with_stacktrace_
     )
     response_json = json.loads(response.content)
     assert "error_code" in response_json
-    assert response_json["error_code"] == ErrorCode.Name(MALFORMED_REQUEST)
+    assert response_json["error_code"] == ErrorCode.Name(BAD_REQUEST)
     assert "message" in response_json
     assert "stack_trace" in response_json
 
@@ -198,7 +198,7 @@ def test_scoring_server_responds_to_invalid_csv_input_with_stacktrace_and_error_
     )
     response_json = json.loads(response.content)
     assert "error_code" in response_json
-    assert response_json["error_code"] == ErrorCode.Name(MALFORMED_REQUEST)
+    assert response_json["error_code"] == ErrorCode.Name(BAD_REQUEST)
     assert "message" in response_json
     assert "stack_trace" in response_json